A framework using Taylor expansions and random projections estimates LLM performance under arbitrary training batch orders from one reference run.
Critical learning periods in deep networks
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Estimating the Effects of Sample Training Orders for Large Language Models without Retraining
A framework using Taylor expansions and random projections estimates LLM performance under arbitrary training batch orders from one reference run.